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Candidates who become Snowflake ARA-C01 certified demonstrate their worth in the Snowflake field. The SnowPro Advanced Architect Certification (ARA-C01) certification is proof of their competence and skills. This is a highly sought-after skill in large Snowflake companies and makes a career easier for the candidate. To become certified, you must pass the SnowPro Advanced Architect Certification (ARA-C01) certification exam. For this task, you need high-quality and accurate SnowPro Advanced Architect Certification (ARA-C01) exam dumps. We have seen that candidates who study with outdated SnowPro Advanced Architect Certification (ARA-C01) practice material don't get success and lose their resources.

Snowflake ARA-C01 exam is a vendor-neutral certification that is recognized globally. It is designed to validate the skills and knowledge of professionals in Snowflake architecture and design, making them more competitive in the job market. Passing the exam demonstrates that a candidate has a deep understanding of Snowflake and can design and implement complex Snowflake solutions with high levels of efficiency, scalability, and security. Overall, the Snowflake ARA-C01 exam is an excellent opportunity for professionals who want to advance their careers in Snowflake architecture and design.

To prepare for the SnowPro Advanced Architect Certification exam, candidates can take advantage of various resources, including Snowflake's official training courses, online forums, and documentation. There are also many third-party resources available, including practice exams and study guides. It is recommended that candidates have at least two years of hands-on experience working with the Snowflake platform before taking the exam.

To be eligible to take the Snowflake ARA-C01 Exam, candidates must have already passed the Snowflake SCA-C01 (SnowPro Core Certification) Exam. The SnowPro Core Certification is the foundation of the SnowPro Certification program and covers the core concepts and skills needed to work with Snowflake. Once a candidate has passed the SnowPro Core Certification, they can then move on to the SnowPro Advanced Architect Certification.

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q71-Q76):

NEW QUESTION # 71
A company has a Snowflake account named ACCOUNTA in AWS us-east-1 region. The company stores its marketing data in a Snowflake database named MARKET_DB. One of the company's business partners has an account named PARTNERB in Azure East US 2 region. For marketing purposes the company has agreed to share the database MARKET_DB with the partner account.
Which of the following steps MUST be performed for the account PARTNERB to consume data from the MARKET_DB database?

A. Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA replicate the database MARKET_DB to AZABC123 and from this account set up the data sharing to the PARTNERB account.
B. From account ACCOUNTA create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then make this database the provider and share it with the PARTNERB account.
C. Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA create a share of database MARKET_DB, create a new database out of this share locally in AWS us- east-1 region, and replicate this new database to AZABC123 account. Then set up data sharing to the PARTNERB account.
D. Create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then replicate this database to the partner's account PARTNERB.

Answer: A

Explanation:
* Snowflake supports data sharing across regions and cloud platforms using account replication and share replication features. Account replication enables the replication of objects from a source account to one or more target accounts in the same organization. Share replication enables the replication of shares from a source account to one or more target accounts in the same organization1.
* To share data from the MARKET_DB database in the ACCOUNTA account in AWS us-east-1 region with the PARTNERB account in Azure East US 2 region, the following steps must be performed:
* Create a new account (called AZABC123) in Azure East US 2 region. This account will act as a bridge between the source and the target accounts. The new account must be linked to the ACCOUNTA account using an organization2.
* From the ACCOUNTA account, replicate the MARKET_DB database to the AZABC123 account using the account replication feature. This will create a secondary database in the AZABC123 account that is a replica of the primary database in the ACCOUNTA account3.
* From the AZABC123 account, set up the data sharing to the PARTNERB account using the share replication feature. This will create a share of the secondary database in the AZABC123 account and grant access to the PARTNERB account. The PARTNERB account can then create a database from the share and query the data4.
* Therefore, option C is the correct answer.
Replicating Shares Across Regions and Cloud Platforms : Working with Organizations and Accounts : Replicating Databases Across Multiple Accounts : Replicating Shares Across Multiple Accounts

NEW QUESTION # 72
When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)

A. Avro
B. XML
C. CSV
D. JSON
E. Parquet

Answer: A,D

Explanation:
The data formats that are supported for the messages when using the Snowflake Connector for Kafka are Avro and JSON. These are the two formats that the connector can parse and convert into Snowflake table rows. The connector supports both schemaless and schematized JSON, as well as Avro with or without a schema registry1. The other options are incorrect because they are not supported data formats for the messages. CSV, XML, and Parquet are not formats that the connector can parse and convert into Snowflake table rows. If the messages are in these formats, the connector will load them as VARIANT data type and store them as raw strings in the table2. Reference: Snowflake Connector for Kafka | Snowflake Documentation, Loading Protobuf Data using the Snowflake Connector for Kafka | Snowflake Documentation

NEW QUESTION # 73
An Architect has chosen to separate their Snowflake Production and QA environments using two separate Snowflake accounts.
The QA account is intended to run and test changes on data and database objects before pushing those changes to the Production account. It is a requirement that all database objects and data in the QA account need to be an exact copy of the database objects, including privileges and data in the Production account on at least a nightly basis.
Which is the LEAST complex approach to use to populate the QA account with the Production account's data and database objects on a nightly basis?

A. 1) Enable replication for each database in the Production account
2) Create replica databases in the QA account
3) Create clones of the replica databases on a nightly basis
4) Run tests directly on those cloned databases
B. 1) In the Production account, create an external function that connects into the QA account and returns all the data for one specific table
2) Run the external function as part of a stored procedure that loops through each table in the Production account and populates each table in the QA account
C. 1) Create a share in the Production account for each database
2) Share access to the QA account as a Consumer
3) The QA account creates a database directly from each share
4) Create clones of those databases on a nightly basis
5) Run tests directly on those cloned databases
D. 1) Create a stage in the Production account
2) Create a stage in the QA account that points to the same external object-storage location
3) Create a task that runs nightly to unload each table in the Production account into the stage
4) Use Snowpipe to populate the QA account

Answer: A

Explanation:
This approach is the least complex because it uses Snowflake's built-in replication feature to copy the data and database objects from the Production account to the QA account. Replication is a fast and efficient way to synchronize data across accounts, regions, and cloud platforms. It also preserves the privileges and metadata of the replicated objects. By creating clones of the replica databases, the QA account can run tests on the cloned data without affecting the original data.
Clones are also zero-copy, meaning they do not consume any additional storage space unless the data is modified. This approach does not require any external stages, tasks, Snowpipe, or external functions, which can add complexity and overhead to the data transfer process.
Reference:
Introduction to Replication and Failover
Replicating Databases Across Multiple Accounts
Cloning Considerations

NEW QUESTION # 74
An Architect Is designing a data lake with Snowflake. The company has structured, semi-structured, and unstructured data. The company wants to save the data inside the data lake within the Snowflake system. The company is planning on sharing data among Its corporate branches using Snowflake data sharing.
What should be considered when sharing the unstructured data within Snowflake?

A. A scoped URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 24-hour time limit for the URL.
B. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with a 7-day time limit for the URL.
C. A file URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with the "expiration_time" argument defined for the URL time limit.
D. A pre-signed URL should be used to save the unstructured data into Snowflake in order to share data over secure views, with no time limit for the URL.

Answer: C

Explanation:
According to the Snowflake documentation, unstructured data files can be shared by using a secure view and Secure Data Sharing. A secure view allows the result of a query to be accessed like a table, and a secure view is specifically designated for data privacy. A scoped URL is an encoded URL that permits temporary access to a staged file without granting privileges to the stage. The URL expires when the persisted query result period ends, which is currently 24 hours. A scoped URL is recommended for file administrators to give scoped access to data files to specific roles in the same account. Snowflake records information in the query history about who uses a scoped URL to access a file, and when. Therefore, a scoped URL is the best option to share unstructured data within Snowflake, as it provides security, accountability, and control over the data access. References:
* Sharing unstructured Data with a secure view
* Introduction to Loading Unstructured Data

NEW QUESTION # 75
An Architect for a multi-national transportation company has a system that is used to check the weather conditions along vehicle routes. The data is provided to drivers.
The weather information is delivered regularly by a third-party company and this information is generated as JSON structure. Then the data is loaded into Snowflake in a column with a VARIANT data type. This table is directly queried to deliver the statistics to the drivers with minimum time lapse.
A single entry includes (but is not limited to):
- Weather condition; cloudy, sunny, rainy, etc.
- Degree
- Longitude and latitude
- Timeframe
- Location address
- Wind
The table holds more than 10 years' worth of data in order to deliver the statistics from different years and locations. The amount of data on the table increases every day.
The drivers report that they are not receiving the weather statistics for their locations in time.
What can the Architect do to deliver the statistics to the drivers faster?

A. Divide the table into several tables for each location by using the location address information from the JSON dataset in order to process the queries in parallel.
B. Add search optimization service on the variant column for longitude and latitude in order to query the information by using specific metadata.
C. Divide the table into several tables for each year by using the timeframe information from the JSON dataset in order to process the queries in parallel.
D. Create an additional table in the schema for longitude and latitude. Determine a regular task to fill this information by extracting it from the JSON dataset.

Answer: B

Explanation:
To improve the performance of queries on semi-structured data, such as JSON stored in a VARIANT column, Snowflake's search optimization service can be utilized. By adding search optimization specifically for the longitude and latitude fields within the VARIANT column, the system can perform point lookups and substring queries more efficiently. This will allow for faster retrieval of weather statistics, which is critical for the drivers to receive timely updates.

NEW QUESTION # 76
......

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